Bibliographic record
Abstract
Abstract In the social, historical, and political context of Xi Jinping’s China, particular forms of racialization and racial capitalism have emerged in Altay Prefecture, the homeland of ethnic Kazakhs on China’s northwest border. This study examines the husbandry industry in Altay Prefecture to elucidate how Xi’s China has built a mode of racial capitalism through the management of Kazakh land, ethnicity, and culture. Within the framework of a case study, I employ document collection and participant observation methods to gather data that are then interpreted through critical policy analysis. The research shows that Kazakhs have been racialized based on their mobile pastoral traditions, enslaved in the “debt economy,” and exploited through husbandry policies and programs. The particular ways in which husbandry has been restructured and assimilated into Chinese industrial production chains exploit and reproduce the Kazakh-Han hierarchy and segregation. This close look at racial capitalism in Altay sheds light on the operations of Xi’s ecological civilization and war on poverty policies in an ethnic minority border region and discusses how they align with the broader geopolitics of the Belt and Road Initiative in Central Asia and Eastern Europe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".